Standard syllabus
R · Graduate · CS / Programming
Topics
R basics
- RStudio workflow; scripts, console, and projects
- Vectors, matrices, lists, and data frames
- Indexing, subsetting, and recycling rules
- Factors, dates, and missing data (NA) handling
- Reading/writing CSV, RDS, and common file formats
Analysis and visualization
- Summary statistics and exploratory data analysis
- Base and ggplot2 graphics: histograms, scatter, faceting
- Hypothesis tests and confidence intervals (intro)
- Linear regression with lm(); model summaries and diagnostics
- dplyr/tidyverse: filter, select, mutate, group_by, summarize
Pricing
Graduate-level rates are set on consultation. See the pricing page for K–12 and undergraduate rates.